HAMLET FP7 GA 218817 Neutron dose assessments for MATROSHKA using the HPA PADC dosemeter Jon Eakins,Luke Hager and Rick Tanner for the HAMLET consortium Health Protection Agency, Centre for Radiation, Chemical and Environmental Hazards, Oxfordshire, England
Overview 2 AIM: HOW? To assess the neutron component of dose onboard the ISS Use HPA PADC dosemeters attached to the poncho of the MATROSHKA phantom PROBLEM: The dosemeter was designed for use within terrestrial workplace neutron fields SOLUTION: Develop techniques to account for the highenergy, many-particle field present
The HPA PADC Dosemeter 3 0.5 mm thick sheet of PADC contained in nylon holder Routine issue for neutron personal dosimetry in workplace fields Calibrated for neutrons ~200 MeV by reference exposures
The HPA PADC Dosemeter 4 Detect neutrons by examining latent tracks of damage in the PADC from secondary particles produced during interactions Electrochemical etch of rear face of dosemeter reveals tracks as countable pits Number of pits is proportional to dose
MATROSHKA 5 HPA PADC dosemeters in poncho worn by MATROSHKA phantom MTR 1 Outside ISS MTR 2A & 2B Inside ISS
Problem Summary 6 NATURE OF PROBLEM: Response to higher energy neutrons (> 200 MeV) not known Response to ion sources also unknown: Ions may produce tracks indistinguishable from those of secondary charged particles created by neutrons So, need to determine how many pits resulted from incident neutrons, and how many from incident protons, helium ions and heavy ions etc. Need to relate the number of neutron tracks to a dose estimate.
General Plan of Attack 7 a) Apply Monte Carlo techniques to determine the neutron and light-ion field within the ISS
General Plan of Attack 8 a) Apply Monte Carlo techniques to determine the neutron and light-ion field within the ISS b) Use this neutron field, with known response characteristics, to estimate the number of neutron pits expected, relative to those from other particles
General Plan of Attack 9 a) Apply Monte Carlo techniques to determine the neutron and light-ion field within the ISS b) Use this neutron field, with known response characteristics, to estimate the number of neutron pits expected, relative to those from other particles c) Separate ion contribution into three components, and in turn: Use calculated hydrogen distributions, calibrations and analytical techniques to estimate the relative contribution from 1 H, 2 H and 3 H Use calculated helium distributions, calibrations and analytical techniques to estimate the relative contribution from 3 He and 4 He Use an additional chemical etch to distinguish HZI pits
General Plan of Attack 10 a) Apply Monte Carlo techniques to determine the neutron and light-ion field within the ISS b) Use this neutron field, with known response characteristics, to estimate the number of neutron pits expected, relative to those from other particles c) Separate ion contribution into three components, and in turn: Use calculated hydrogen distributions, calibrations and analytical techniques to estimate the relative contribution from 1 H, 2 H and 3 H Use calculated helium distributions, calibrations and analytical techniques to estimate the relative contribution from 3 He and 4 He Use an additional chemical etch to distinguish HZI pits d) Consider the ratios of the above, and compare with the total number of pits actually measured to determine the neutron contribution to dose
11 1) Monte Carlo Calculation of Neutron and Light-ion Field
Summary 12 AIM: To determine the fluence-energy distributions of n, p, d, t, 3 He and 4 He particles within the ISS as a result of cosmic rays impinging on its structure METHOD: Use CREME96 to generate primary input spectra Use MCNPX_2.6.0 to transport these through shielding
CREME96 13 Flight data file corresponding to 1 st April 2008 was used to estimate average orbit parameters for ISS, such as orientation, min/max altitude, and period of the orbit etc. Assumed sufficiently typical of the MATROSKA 2B phase as a whole Solar minimum conditions assumed
CREME96 Output 14 Assume terrestrial isotopic compositions Limit attention to H-1, He-4, C-12 and O-16 sources
MCNPX Modelling 15 Transport of n, p, d, t, 3 He, 4 He, HZI, π 0,±, K 0,±, γ, particles Mix of models: LAQGSM, CEM, ISABEL, FLUKA QGS, Output binned according to requirements of PADC analysis Repeated for 1 H, 4 He, 12 C and 16 O sources
MCNPX Results 16 Fluence rate (cm -2 s -1 sr -1 MeV -1 ) 10-1 10-2 10-3 10-4 10-5 10-6 10-7 10-8 10-9 10-10 10-11 10-12 Neutron Proton Deuteron Triton Helion Alpha 10-2 10-1 10 0 10 1 10 2 10 3 10 4 10 5 Energy (MeV) (Uncertainties reflect statistical variation of MC method only )
Estimate of Uncertainty 17 Parameter variation tests performed: Shield density / thickness varied PP vs. Isotropic sources Modelling of a more realistic shielding geometry (Zvezda) Impact of model choice LAQGSM vs FLUKA QGS test performed for 12 C Effect of cosmic photon field shown to be negligible But primary leptons could not be considered Overall uncertainty is??? (but hopefully accurate to within an order of magnitude or so)
Intercomparison 18 Uncertainties and ambiguities make comparison of results with previous research useful Compare MCNPX data with those from: Ersmark*, who used GEANT4 to transport protons through an accurate model of the Columbus module Sato et al**., who used PHITS_2.16 to transport particles through 15 g/cm 2 of aluminium at altitude of 380 km * Ersmark T (2006a). Geant 4 Monte Carlo simulations of the International Space Station radiation environment. Doctoral thesis. Royal Institute of Technology: Stockholm. ** Sato T, A Endo, L Sihver and K Niita (2011a). Dose estimation for astronauts using dose conversion coefficients calculated with the PHITS code and the ICRP/ICRU adult reference computational phantoms. Radiat Environ Biophys 50, 115-123.
Intercomparison Results(Neutrons) 19 0.25 Ersmark calculated Columbus Module model 3 with ISS (GEANT4) Sato 380km 15 g cm -2 aluminium ISS model (PHITS) Eakins 350km 20 g cm -2 duraluminium slab shield (MCNPX) Acceptable agreement between neutron fields Fluence normalized to unity, per ln( E) 0.20 134 (16) msv -1 Dosemeter E ISO { Response 124 (15) msv -1 102 (12) msv -1 0.15 0.10 0.05 0 0.01 0.1 1 10 100 10 3 10 4 Neutron energy, E (MeV) Can repeat all analyses in subsequent work using the 3 different datasets Interpret envelope function of obtained results as an estimate of their uncertainty
Outcomes 20 Monte Carlo results assumed to provide a reasonable estimate of neutron and light-ion field inside ISS during the MATROSHKA 2B phase Assumed also representative of the field during the MATROSHKA 2A phase Use the same MC datasets in both cases For unshielded MATROSHKA 1 dosemeters, suggest use of raw CREME output Easily recalculated using appropriate mission data
21 2) Estimate of Neutron Fraction
General Method 22 a) Convolve MC-calculated neutron fluence rate distribution inside ISS with fluence-response characteristics of dosemeter b) Divide each bin by total fluence rate to obtain energy-binned relative distribution of pits per-appliedfluence c) Correct for efficiency / linearity / background etc. to obtain final distribution of pits expected per-appliedfluence
Fluence-Response 23 2 Neutron fluence spectrum (Eakins: 20 g cm -2 duraluminium slab) Dosemeter R Φ (experimentally determined) ISO Dosemeter R Φ (extrapolated) ISO Dosemeter Reading (pits) PROBLEM: Dosemeter not calibrated above ~200 MeV Arb. units 1 SOLUTION: Assume response characteristic flat >200 MeV Errors introduced by this hoped acceptable, as most of the neutron spectrum is <200 MeV 0 0.01 0.1 1 10 100 10 3 10 4 Neutron energy (MeV) Find majority of signal is in ~1 MeV to ~100 MeV range
Results 24 Integrate over all bins to determine MC-derived neutron count rate: Neutron energy distribution Total neutron fluence rate (cm -2 s -1 ) R Φ (10-6 cm 2 ) Calculated neutron pit rate (10-5 s -1 ) Eakins 1.3548 37.3 5.05 Ersmark 2.9985 30.7 9.21 Sato 3.3551 34.2 11.47 Mean (std. uncertainty) 8.58 (1.88) Use mean value with mission data to estimate relative neutron contributions: MTR Phase Calculated neutron pit rate (10-5 s -1 ) Phase duration (d) Calculated neutron pits on detector, C Z=0 MTR-1 8.58 (1.88) 619 4589 (1005) MTR-2A 8.58 (1.88) 367 2721 (596) MTR-2B 8.58 (1.88) 417 3091 (677)
25 3) Estimate of Heavy Ion (Z>2) Fraction
Background 26 PADC dosemeter responds to charged particles that: o Impinge on the dosemeter at angles less than a critical value o Deposit energy in the etched volume of the detector with linear energy transfer (LET, PADC ) greater than a threshold value o Exceed this threshold over the entire etched range Theoretical considerations, supported by irradiations with 4 He and 20 Fe ions at the HIMAC facility, have found this critical angle to be ~60 to the normal this LET threshold to be ~40-60 kev µm -1 and this etched range to be ~1µm
Particle Dependency 27 Converting: 10 3 Can produce tracks on both faces Cannot produce tracks on both faces x = 5 x = 6 x = 4 x = 3 x = 2 x = 1 6 Li 7 Li 9 Be LET Energy Range Criteria satisfied differently by different particle species CSDA range (µm) 10 2 d t 3 He 4 He e.g. protons must have an energy >0.05 MeV but <0.6 MeV for a pit to form Can plot E max vs Z and R crit vs Z 10 1 p 10-1 10 0 10 1 10 2 Ion energy, E max (MeV) Find most Z>2 particles that meet criteria have ranges that exceed the 0.5mm thickness of the dosemeter
HZI Distinction 28 Particles with Z > 2 likely to produce an etchable damage track through the entire thickness of the dosemeter But, no particle with Z 2 produces an etchable damage track through the entire thickness of the dosemeter Distinguish pits from Z > 2 particles by observing whether it passed straight through the PADC Achievable by performing a second (chemical) etch on both faces of the detector, and observing how many of the features on the rear face pair with ones on the front face
Pit Pairing 29 Observe rear and front faces of doubly-etched dosemeter under microscope: Count total no. of pits on rear face, N Count number of paired pits, h Divide to find fraction of pits from Z > 2 particles, (h/n) Find HZI contribute, on average, ~4.3 (±1.0) pits per day to dosemeter
30 4) Estimate of Hydrogen & Helium Fractions
LET Thresholds 31 Need to know LET thresholds of Z=1 and Z=2 particles: Approximate functional form of LET threshold as varying with 1/(cosine of angle from normal) Just require normal incidence LET thresholds Can calculate LET thresholds by considering the etchable ranges of particles Calculate etchable ranges of particles by considering the depth-dose profiles of pits through a stack of PADC dosemeters
HIMAC Exposures(Protons) 32 PADC dosemeter stacks exposed at the HIMAC facility Net Corrected Pits on detector 12000 11000 10000 9000 8000 7000 6000 5000 4000 3000 2000 40 MeV proton 70 MeV proton 1000 0 0 5 10 15 20 25 30 35 40 Distance in PADC (mm)
HIMAC Exposures(Helium) 33 Exposed at 0, 40, 50 and 60 to normal 350 Net Corrected pits (cm -2 ) 300 250 200 150 100 (0 ) 50 0 2 4 6 8 10 12 14 16 Distance into PADC stack (mm)
Etchable Ranges 34 Pits relate to particles that satisfied the conditions required to form an etchable track: Let R crit be the range over which the LET of a particle is such that it could cause sufficient damage to induce a pit A pit will be formed if this range spans the etchable volume of the dosemeter... If crosses boundary
Etchable Ranges 35 Can calculate R crit by counting the pits Expect: N = R crit D Φ where N is the total number of pits summed over all dosemeters Convert: R crit E crit LET crit Find 0 LET thresholds of 44 kev/µm for Z=1 and 58 kev/µm for Z=2 LET thresholds at different angles derived from these
MATROSHKA Exposures 36 Must determine how many pits on the dosemeters resulted from incident hydrogen and helium ions Assume an etchable track is formed if the ion arrives at the etched (rear) face of the PADC with appropriate LET Need to know the fluence rates of Z=1 and Z=2 particles of sufficient LET at this location The issue is complicated by the anisotropy of the exposure conditions
Simplified MATROSHKA Geometry 37 Envisage geometry as dosemeter adjacent to a 30cm diameter sphere of ICRU 4-element tissue: Assume configuration is exposed isotropically to the calculated ISS field Etchable track may form if particle impinges on rear face with suitable LET i.e. if particle impinges on sphere or dosemeter front with suitable energy such that it then impinges on rear face with the suitable LET
Particles Impinging on the Sphere 38 Assume particles travel through sphere in straight lines For particle impinging at angle θ, chord length through sphere is d cos(π-θ) where d = 30cm For given angle θ, use range-energy tables (SRIM) to calculate energies of particles that have sufficient LET after d cos(π-θ) of tissue Use Monte Carlo data to estimate fluence rates of such particles inside ISS (MATROSHKA 2A+B) or CREME96 data outside ISS (MATROSHKA 1) Process is repeated for all angles (in bins) between 2π/3 and π for all Z=1 ions (p,d and t) and all Z=2 ions ( 3 He and 4 He)
Dosemeter Front 39 Consider particles travelling through model of dosemeter material and surrounds (MATROSHKA container, poncho, etc.): If particles travel in straight lines, path length through surrounds is [D / cos(θ)] where D is tissue-equivalent thickness of the material For given angle θ, use range-energy tables (SRIM) to calculate energies of particles that have sufficient LET after [D / cos(θ)] of tissue Use Monte Carlo (2A &2B) or CREME (1) data to estimate fluence rates of such particles Process is repeated for all angles (in bins) between 0 and π/3 for all Z=1 ions (p,d and t) and all Z=2 ions ( 3 He and 4 He)
Results 40 Analyse data to estimate expected rate of pit formation: Particle type MTR-1 (d -1 ) MTR-2A, 2B (d -1 ) Z = 1 16.4 (9.0) 1.58 (0.46) Z = 2 0.035 (0.036) 0.027 (0.024) Apply MATROSHKA phase durations to estimate relative particle contributions: Particle Type Hydrogen (C Z=1 ) Number of Pits MTR-1 MTR-2A MTR-2B 8981(5579) 580 (169) 659 (192) Helium (C Z=2 ) 22 (22) 10 (9) 11 (10)
5) Final Results 41
Pit Distinction 42 Bring together data from the various research streams to derive the overall doses from neutrons GENERAL METHOD: If a dosemeter has N pits after processing: i. Subtract number of coincidence (i.e. HZI-caused) pits ii. iii. Proportion remainder according to relative contributions expected from neutrons, hydrogen ions and helium ions Relate the neutron-induced pits to an estimate of dose rate
HZI Subtraction 43 - N Z<3 Where N is the total number of pits on a dosemeter And h is the number of paired-pits N Z<3 is the number of pits attributable to neutrons, hydrogen and helium N h =N Z<3
Proportion Remainder 44 If C Z=0 is the relative contribution from neutrons (i.e. the result from Section 2) If C Z=1 and C Z=2 are the relative contributions from hydrogen and helium ions respectively (i.e. the results from Section 4) Then, number of pits attributable from neutrons, N neutrons, is calculable: N neutron = Z = 0 N < 3 C = 0 + = 1 + Z Z CZ CZ = 2 C (N.B. This ratio method should cancel out some of the systematic uncertainties inherent in the calculations of C Z=0, C Z=1 and C Z=2 )
Neutron Pits 45 Gives final estimate of neutron-induced pits: Phase Total Pits, N Remainder Pits, N Z<3 Neutron Pits, N neutron MTR-1 19642 (686) 16980 (924) 5733 (2719) MTR-2A 9354 (154) 7776 (398) 6390 (1870) MTR-2B 8192 (126) 6399 (436) 5259 (1557)
Dose Quantities 46 Need to convert pit-count to an estimate of dose GENERAL METHOD: a) Convolve neutron response with fluence-to-dose conversion coefficients distribution (binned using common energy grid) Provides dose distribution signal b) Integrate over all bins to give final estimate of dose Easy for E ISO, but for operational dose quantities there is a lack of suitability and availability of data at high energies Had to derive conversion coefficients for H p (10,ISO)
Recorded Doses 47 Applying mean dose-per-count data to measured neutron count data provides final dose results: Phase E ISO (msv) (a) Dose Rate (µsv/d) (a) H p (10, ISO) (msv) (b) Dose Rate (µsv/d) (b) MTR-1 48 (23) (c) 78 (37) (c) 58 (28) (c) 94 (45) (c) MTR-2A 53 (17) (c) 145 (46) (c) 65 (21) (c) 177 (57) (c) MTR-2B 44 (14) (c) 106 (34) (c) 53 (17) (c) 127 (41) (c) a) UsingE ISO calibration of 120 (14) msv -1 b) UsingH p (10, ISO) calibration of 99 (12) msv -1 c) Combined standard uncertainty
Acknowledgements 48 Irradiations at HIMAC have been performed within HIMAC Research Project #20P240, Space Radiation Dosimetry-Ground Based Verification of the MATROSHKA Facility. The 40 and 70 MeV proton irradiations were performed in collaboration with Yukio UCHIHORI (PhD) and colleagues, NIRS, Chiba, Japan. The HAMLET project has received funding from the European Community's Seventh Framework Programme (FP7) under grant agreement 218817.
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CREME Limitations 53 GCR environment in FLUX: - archaic vs magnetically unshielded GTRN: bespoke vs pre-calculated } Small Impact? User data: Orbit averages from limited dataset e.g. altitude variation field variation } Medium Impact? Model limitations and accuracy: - Accuracy of underlying datasets and models? - Uncertainties? - CREME96 vs SPENVIS?? etc. }??? Impact
MCNPX Limitations 54 Model of ISS is VERY basic effects of shape, materials, anisotropies etc. unknown 1 TeV truncation of 12 C and 16 O primary fields Accuracy of models debateable: o Underlying data limited o Theory not always well understood o No uncertainties, Runtime problems
Dose Quantities 55 Need to convert pit-count to an estimate of dose GENERAL METHOD: a) Convolve neutron response with fluence-to-dose conversion coefficients distribution (binned using common energy grid) Provides dose distribution signal b) Integrate over all bins to give final estimate of dose
Dose Quantities 56 Problems at high energies due to: 1) Lack of conversion coefficient data; 2) Lack of appropriateness of dose quantities Conversion coefficients for ambient dose equivalent [H*(10)] and effective dose in isotropic fields [E ISO ] are available in ICRU 57 up to 20 MeV, and extended to 10 TeV by Pelliccioni* But, it may be suggested that using H*(10) is not ideal, as considering a depth of 10 mm in an expanded and aligned high-energy field is inappropriate - e.g. H*(10) underestimates E ISO at 10 GeV by an order of magnitude Instead, suggest that it is the H p (10,ISO) response of the dosemeter that should be used for operational protection * Pelliccioni M (2000). Overview of fluence-to-effective dose and fluence-to-ambient dose equivalent conversion coefficients for high energy radiation calculated using the FLUKA code. Radiat Prot Dosim, 88 (4), 279 297.
Personal Dose Equivalent 57 BUT: No [H p (10,ISO)/Φ] dataset available 5 MCNP4c2 used to calculate H p (10,ISO)/Φ up to 20 MeV 3 2 H*(10)/E ISO H p (10, ISO) = 1.3E ISO Difficult >20 MeV due to lack of data on quality factors Ratio 1 0.7 H p (10,ISO) HPA /E ISO Instead, assume the ratio [H p (10,ISO) : E ISO ] remains constant >20 MeV 0.5 0.3 Implies that H p (10,ISO) is a conservative estimate of E ISO 0.2 k.h*(10)/e ISO k = H p (10, ISO) HPA /H*(10) for E n = 20 MeV 0.1 10-3 10-2 0.1 1 10 100 10 3 10 4 10 5 10 6 10 7 10 8 10 9 10 10 Neutron energy, E n (ev) Using H*(10) instead could give underestimate of E ISO at high energies
Dose Response 58 Dosemeter reading per dose in an energy interval (msv -1 ) 300 250 200 150 100 50 0 0.01 0.1 1 10 100 10 3 10 4 Neutron energy (MeV) Dosemeter R E(ISO) Dosemeter R Hp (10,ISO) Dosemeter R H*(10) Folding: Fluence-response of d dosemeter; Fluence-to-dose d conversion coefficient data provides E ISO and H p (10,ISO) readings per energy interval [ For completeness, the H*(10) response of the dosemeter is also shown ]
Neutron Effective Dose 59 Contributions from all energy bins are summed to give the total dose responses Uncertainties derived by repeating for the 3 neutron distributions, and considering envelope function of results
Neutron Personal Dose Equivalent 60 Contributions from all energy bins are summed to give the total dose responses Uncertainties derived by repeating for the 3 neutron distributions, and considering envelope function of results